Research Computer Scientist: RF/EW ML Architect

Southwest Research Institute; Dayton (OH); On-site; USD 110,000 - 160,000; Full time

Job summary

Southwest Research Institute’s Spectrum Innovation section develops neural network models for electronic warfare, including real-time RF signal classification and automated countermeasures. You’ll build synthetic data pipelines and validate datasets to train and test mission-critical algorithms for edge deployment.

You’ll assess new ML frameworks, communicate risks and performance in reviews, and work with systems and embedded engineers to containerize models for modular, edge-ready solutions in

Qualifications

• Bachelor's or Master's in Electrical/Computer Engineering, CS, Data Science with ML/Signal Processing focus.
• 4-8 years hands-on DL modeling using PyTorch or TensorFlow with complex data.
• 3 years end-to-end data pipelines including synthetic data and data quality validation.
• 3 years technical communication, including evaluation reports and design reviews.
• 1 year ML applied to DSP/RF/ECW domains.
• Valid driver’s license.

Responsibilities

• Design, train, optimize, and profile custom deep learning architectures for RF signal characterization.
• Develop, preprocess, and validate multi-sensor RF/EW datasets via synthetic generation and HWIL.
• Benchmark, review, and report on ML architectures; deliver evaluation reports and recommendations.
• Prepare progress briefings and demos; collaborate with cross-functional teams for edge deployment.
• Collaborate with systems/embedded engineers to containerize models for modular edge compute.

Skills

Machine learning

Signal processing

Technical communication

Education

Bachelor's or Master's in Electrical Engineering, Computer Engineering, Computer Science, Data Science

Tools

PyTorch

TensorFlow

Python

Job description

Southwest Research Institute’s Spectrum Innovation section develops neural network models for electronic warfare, including real-time RF signal classification and automated countermeasures. You’ll build synthetic data pipelines and validate datasets to train and test mission-critical algorithms for edge deployment.

You’ll assess new ML frameworks, communicate risks and performance in reviews, and work with systems and embedded engineers to containerize models for modular, edge-ready solutions in